Policy Publication
Soybean Aphid and Changing Pesticide Usage in Iowa
Agricultural Policy Review Fall 2025. Center for Agricultural and Rural Development, Iowa State University.
PhD Candidate in Economics, Iowa State University
I am a PhD candidate in Economics at Iowa State University, with a focus on production economics and environmental economics.
My work studies agricultural and environmental decision-making, including costly information acquisition, pesticide use, conservation practices, and farmland valuation.
Policy Publication
Agricultural Policy Review Fall 2025. Center for Agricultural and Rural Development, Iowa State University.
Publication
Journal of Environmental Policy and Administration, 29(3), 49-75. In Korean.
Working Paper
Integrated Pest Management (IPM) is built around a simple operational rule: scout the field, compare pest density to an economic threshold, and spray only when expected damage exceeds the cost of control. A broad literature documents that threshold-based recommendations are unevenly implemented in practice, citing limited familiarity with IPM principles, uncertainty about localized effectiveness, and the time and cost of field monitoring as recurring barriers. Soybean aphid management in the U.S. Midwest reflects this pattern: foliar spraying responds only weakly to realized pest pressure, farmer-level management rules are persistent and heterogeneous, and many growers rely on prophylactic neonicotinoid seed treatments that bypass early within-season scouting.
This paper embeds costly and imperfect scouting directly into the economic-threshold framework. Farmers hold prior beliefs over latent short-run aphid growth, choose whether to acquire information through scouting, update beliefs if scouting occurs, and then decide whether to spray. The model jointly determines the treatment and information margins and shows that the densities at which information could change the spray decision need not be densities at which a grower would privately pay to acquire it. Calibrated to pesticide-use survey data, untreated-plot aphid data, and observed custom rates, the model implies a season-level value of growth-state information with a mean of $0.25 and a maximum of $3.17 per acre, against a monitoring cost of $4.61. The value lies below the cost in every observed plot-season. A perfect full-field benchmark shows that exact density-path and timing information can be valuable in high-pressure environments, yet an imperfect path monitor at benchmark reliability yields incremental values below observed monitoring costs across public-information cells. What monitoring is worth depends on what it reveals: a signal that only sharpens the short-run growth outlook is the low-value one, while richer density-path information is worth more but, when imperfect, still does not cover its cost. The margin that binds is a joint one, set by monitoring cost, signal precision, and information content together. As monitoring technology lowers costs and improves signal quality, scouting becomes the default mode of management where information can change the action.
Work in Progress
Work in Progress